[PDF.88tl] Radial Basis Function Networks 2: New Advances in Design (Studies in Fuzziness and Soft Computing) (v. 2)
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Radial Basis Function Networks 2: New Advances in Design (Studies in Fuzziness and Soft Computing) (v. 2)
Robert J. Howlett, Lakhmi C. Jain
[PDF.fw80] Radial Basis Function Networks 2: New Advances in Design (Studies in Fuzziness and Soft Computing) (v. 2)
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| #13730460 in Books | Physica | 2001-04-27 | Original language:English | PDF # 1 | 6.14 x.88 x9.21l,1.57 | File type: PDF | 360 pages | ||From the Back Cover|The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused
The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a v...
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